Biomarkers Predictive of Survival and Response to Immune Checkpoint Inhibitors in Melanoma
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Published on: February 25, 2020
Emanuelle M Rizk1, Angelina M Seffens2, Megan H Trager2
1Department of Medicine, Columbia University Irving Medical Center, 630 West 168th Street, P&S 9-428, New York, NY, 10032, USA.
Abstract:
Immunotherapy has revolutionized the treatment of melanoma. Targeting of the immune checkpoints cytotoxic T-lymphocyte-associated protein 4 and programmed cell death protein 1 has led to improved survival in a subset of patients. Unfortunately, the use of immune checkpoint inhibitors is associated with significant side effects and many patients do not respond to treatment. Thus, there is an urgent need both for prognostic biomarkers to estimate risk and for predictive biomarkers to determine which patients are likely to respond to therapy. In this review, prognostic and predictive biomarkers that are an active area of research are outlined. Of note, certain transcriptomic signatures are already used in the clinic, albeit not routinely, to prognosticate patients. In the predictive setting, programmed cell death protein ligand 1 expression has been shown to correlate with benefit but is not precise enough to be used as an exclusionary biomarker. Future investigation will need to focus on biomarkers that are easily reproducible, cost effective, and accurate. The use of readily available clinical material, such as serum or hematoxylin and eosin-stained images, may offer one such path forward.
Insights
Immunotherapy improves melanoma survival, but side effects and non-response necessitate better biomarkers. Research focuses on prognostic and predictive markers for personalized melanoma treatment and risk assessment.
Area of Science:
- Oncology
- Immunology
- Biomarker Research
Background:
- Immunotherapy, particularly immune checkpoint inhibitors (ICIs) targeting CTLA-4 and PD-1, has transformed melanoma treatment.
- Despite improved survival for some, ICIs cause significant side effects, and many patients do not respond.
- There is a critical need for biomarkers to predict treatment response and patient prognosis in melanoma.
Purpose of the Study:
- To review current research on prognostic and predictive biomarkers for melanoma.
- To highlight the potential of novel biomarkers for personalized immunotherapy strategies.
- To discuss the requirements for future biomarker development in melanoma.
Main Methods:
- Review of existing literature on melanoma prognostic and predictive biomarkers.
- Analysis of transcriptomic signatures and protein expression (e.g., PD-L1).
- Exploration of potential biomarker sources like serum and H&E-stained images.
Main Results:
- Transcriptomic signatures show potential for prognostication in melanoma patients.
- PD-L1 expression correlates with benefit from immunotherapy but lacks specificity for patient selection.
- Current biomarkers are insufficient for routine clinical decision-making.
Conclusions:
- Accurate prognostic and predictive biomarkers are crucial for optimizing melanoma immunotherapy.
- Future biomarkers must be reproducible, cost-effective, and accurate.
- Utilizing accessible clinical materials like serum or tissue images presents a promising avenue for biomarker discovery.
